dorsal/arxiv
View SchemaStatistical randomization test for QCD intermittency in a single-event distribution
| Authors | Leif E. Peterson |
|---|---|
| Categories | |
| ArXiv ID | physics/0404016 |
| URL | https://arxiv.org/abs/physics/0404016 |
Abstract
A randomization test was developed to determine the statistical significance of QCD intermittency in single-event distributions. A total of 96 simulated intermittent distributions based on standard normal Gaussian distributions of size N=500, 1000, 1500, 2000, 4000, 8000, 16000, and 32000 containing induced holes and spikes were tested for intermittency. Non-intermittent null distributions were also simulated as part of the test. A log-linear model was developed to simultaneously test the significance of fit coefficients for the y-intercept and slope contribution to ln(F_2) vs. ln(M) from both the intermittent and null distributions. Statistical power was also assessed for each fit coefficient to reflect the proportion of times out of 1000 tests each coefficient was statistically significant, given the induced effect size and sample size of the Gaussians. Results indicate that the slope of ln(F_2) vs. ln(M) for intermittent distributions increased with decreasing sample size, due to artificially-induced holes occurring in sparse histograms. For intermittent Gaussians with 4000 variates, there was approximately 70% power to detect a slope difference of 0.02 between intermittent and null distributions. For sample sizes of 8000 and greater, there was more than 70% power to detect a slope difference of 0.01. The randomization test performed satisfactorily since the power of the test for intermittency decreased with decreasing sample size. Power was near-zero when the test was applied to null distributions. The randomization test can be used to establish the statistical significance of intermittency in empirical single-event Gaussian distributions.
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"abstract": "A randomization test was developed to determine the statistical significance\nof QCD intermittency in single-event distributions. A total of 96 simulated\nintermittent distributions based on standard normal Gaussian distributions of\nsize N=500, 1000, 1500, 2000, 4000, 8000, 16000, and 32000 containing induced\nholes and spikes were tested for intermittency. Non-intermittent null\ndistributions were also simulated as part of the test. A log-linear model was\ndeveloped to simultaneously test the significance of fit coefficients for the\ny-intercept and slope contribution to ln(F_2) vs. ln(M) from both the\nintermittent and null distributions. Statistical power was also assessed for\neach fit coefficient to reflect the proportion of times out of 1000 tests each\ncoefficient was statistically significant, given the induced effect size and\nsample size of the Gaussians. Results indicate that the slope of ln(F_2) vs.\nln(M) for intermittent distributions increased with decreasing sample size, due\nto artificially-induced holes occurring in sparse histograms. For intermittent\nGaussians with 4000 variates, there was approximately 70% power to detect a\nslope difference of 0.02 between intermittent and null distributions. For\nsample sizes of 8000 and greater, there was more than 70% power to detect a\nslope difference of 0.01. The randomization test performed satisfactorily since\nthe power of the test for intermittency decreased with decreasing sample size.\nPower was near-zero when the test was applied to null distributions. The\nrandomization test can be used to establish the statistical significance of\nintermittency in empirical single-event Gaussian distributions.",
"arxiv_id": "physics/0404016",
"authors": [
"Leif E. Peterson"
],
"categories": [
"physics.data-an"
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"title": "Statistical randomization test for QCD intermittency in a single-event distribution",
"url": "https://arxiv.org/abs/physics/0404016"
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